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Image captcha cropping using symbols (ICS) /
Patent Number: 202041010986, Application: Dr.K.Suresh Kumar.
Web Security invention has grownup extremely vital over the years as the internet has become the place for the behavior of business in today's world. Numerous attacks stated worldwide that hamper web security by creating a substantial threat to appreciate user data. One amid them is a phishing attack. It is a technique by which an attacker attempts to snip vital data such as user names, PINs, and other private facts by constructing fake websites and cover them as if they remained legitimate ones. -
Image and signal processing in the underwater environment
To handle submerged action recognition, researchers must first understand the fundamental principles of photonic crystals mostly in the liquid phase. Deterioration effects are produced by the mediums physical attributes, which are not present in typical pictures captured in the air because light is increasingly reduced as it passes through water, submarine pictures are characterized by low readability. As a consequence, the sceneries are poorly contrasting and murky. Its vision capability is limited to approximately twenty meters in clear blue water and five meters or less in muddy water due to light dispersion. Absorbing (the removal of incident light) and dispersion are the two factors that produce light degradation. So the actual quality of submersible digital imaging is influenced by the destructive interference processes of light in water. Longitudinal scattered (haphazardly diverted light traveling from objects to the cameras) causes picture details to be blurred. 2021, SciTechnol, All Rights Reserved. -
Image Analysis of MRI-based Brain Tumor Classification and Segmentation using BSA and RELM Networks
Brain tumor segmentation plays a crucial role in medical image analysis. Brain tumor patients considerably benefit from early discovery due to the increased likelihood of a successful outcome from therapy. Due to the sheer volume of MRI images generated in everyday clinical practice, manually isolating brain tumors for cancer diagnosis is a challenging task. Automatic segmentation of images of brain tumors is essential. This system aimed to synthesize previous methods for BSA-RELM-based brain tumor segmentation. The proposed methodology rests on four fundamental pillars: preprocessing, segmentation, feature extraction, and model training. Filtering, scaling, boosting contrast, and sharpening are all examples of preprocessing techniques. When doing segmentation, a clustering technique based on Fuzzy Clustering Means (FCM) is used to breakdown the overall dataset into numerous subsets. The proposed approach used the region of filling for feature extraction. After that, a BSA-RELM is used to train the models with the input features. The proposed technique outperforms BSA and RELM, two of the most common alternatives. There was a 98.61 percent success rate with the recommended method. 2023 IEEE. -
IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques
In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indi-cator of diabetic retinopathy. With that in mind, the purpose of this work is to cre-ate an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine (SVM)-based classification to separate normal and abnormal fundus images at the first level. The input pictures for SVM are pre-processed with Green Channel Extraction and the retrieved features are based on Gray Level Co-occurrence Matrix (GLCM). Furthermore, the presence of Exudate and Diabetic Retinopathy (DR) in fundus images is detected using the Adaptive Neuro Fuzzy Inference System (ANFIS) classifier at the second level of classification. Exudate detection, blood vessel extraction, and Optic Disc (OD) detection are all processed to achieve suitable results. Furthermore, the second level processing comprises Morphological Component Analysis (MCA) based image enhancement and object segmentation processes, as well as feature extraction for training the ANFIS clas-sifier, to reliably diagnose DR. Furthermore, the findings reveal that the proposed model surpasses existing models in terms of accuracy, time efficiency, and precision rate with the lowest possible error rate. 2023, Tech Science Press. All rights reserved. -
ILeHCSA: an internet of things enabled smart home automation scheme with speech enabled controlling options using machine learning strategy
Nowadays, communication schemes and the related automation logics have improved drastically, and people are moving from classical to intelligent applications. This naturally raises the growth ratio of the automation industry and enables researchers to work accordingly. The field of automation is essential in specific unavoidable environments such as hospitals, industrial units, individual residences, disaster areas, etc. In this paper, a novel machine-learning enabled speech-based home automation system is designed, called Intelligent Learning-enabled Home Controlling with Speech Assistance (ILeHCSA). This scheme integrates several latest technologies to control the home intelligently, including machine learning, speech assistance technology, and Internet of Things (IoT) support. Based on these advanced technologies, the logic of smart home automation systems has been designed in this approach, and it provides intellectual home controlling options to people. The following are the devices and sensors which are essential to control the electronic devices embedded into the home environment: Node Microcontroller Unit (MCU) Wi-Fi enabled Microcontroller, Relay Unit, Voice Capture Module with Mic, Speech-to-Text (STT) Converter Module, and Global Positioning System (GPS) to identify the location of the device. The machine-learning logic is utilized to provide a statistical analysis of device usage and to provide a clear summary and traces to maintain the device accordingly. These smart technologies can innovatively change the living atmosphere with sufficient support and comfort. The main intention of this paper is to provide a robust home automation system to support people efficiently, especially the people who are physically suffering from illness and the aged ones. The proposed work provides a 96.5% accuracy ratio when compared with other methods. 2021 Nismon Rio Robert et al. -
IIRM: Intelligent Information Retrieval Model for Structured Documents by One-Shot Training Using Computer Vision
Various information retrieval algorithms have matured in recent years to facilitate data extraction from structured (with a predefined template) digital document images, primarily to manage and automate different organizations invoice and bill reimbursement processes. The algorithms are designated either rule-based or machine-learning-based. Both approaches have respective advantages and disadvantages. The rule-based algorithms struggle to generalize and need periodic adjustments, whereas machine learning-based supervised approaches need extensive data for training and substantial time and effort for manual annotation. The proposed system attempts to address both problems by providing a one-shot training approach using image processing, template matching, and optical character recognition. The model is extensible for any structured documents such as closing disclosure, bill, tax receipt, besides invoices. The model is validated against six different structured document types obtained from a reputed title insurance (TI) company. The comprehensive analysis of the experimental results confirms entity-wise extraction accuracy between 73.91 and 100% and straight through pass 81.81%, which is within business acceptable precision for a live environment. Out of total 32 tested entities, 17 outperformed all state-of-the-art techniques, where max accuracy has been 93 % with only invoices or sales receipts. The system has been set operational to assist the robotic process automation of the TI mentioned above based on the experimental results. 2022, King Fahd University of Petroleum & Minerals. -
IEEHR: Improved Energy Efficient Honeycomb Based Routing in MANET for Improving Network Performance and Longevity
In present scenario, efficient energy conservation has been the greatest focus in Mobile Adhoc Networks (MANETs). Typically, the energy consumption rate of dense networks is to be reduced by proper topological management. Honeycomb based model is an efficient parallel computing technique, which can manage the topological structures in a promising manner. Moreover, discovering optimal routes in MANET is the most significant task, to be considered with energy efficiency. With that motive, this paper presents a model called Improved Energy Efficient Honeycomb based Routing (IEEHR) in MANET. The model combines the Honeycomb based area coverage with Location-Aided Routing (LAR), thereby reducing the broadcasting range during the process of path finding. In addition to optimal routing, energy has to be effectively utilized in MANET, since the mobile nodes have energy constraints. When the energy is effectively consumed in a network, the network performance and the network longevity will be increased in respective manner. Here, more amount of energy is preserved during the sleeping state of the mobile nodes, which are further consumed during the process of optimal routing. The designed model has been implemented and analyzed with NS-2 Network Simulator based on the performance factors such as Energy Efficiency, Transmission Delay, Packet Delivery Ratio and Network Lifetime. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
IDS for Internet of things (IoT) and Industrial IoT Network
The Internet of Things (IoT) is a swiftly increasing domain of interconnected gadgets, technologies, and structures that may be achieved in a small, tightly associated environment or can travel across big geographic areas, including Smart Cities. IoT devices are increasingly deployed for numerous goals inclusive of records sensing, accumulating, and controlling. The IoT enhances user affairs by permitting a huge variety of smart gadgets to link and possible information. IoT gadgets are hastily evolving universally while IoT offerings have become pervasive. IoT devices include a big assortment of devices, along with small, embedded sensors, AI assistants, digital cameras, and so on, which can be found in various backgrounds, i.e., Smart Homes, Smart Communities, and Smart Cities. Smart Cities have developed into intriguing areas with technologies consisting of traffic-conscious streetlights which dynamically react to emergencies by editing site visitors styles. Moreover, with the adoption of 5G networks, technologies and techniques throughout towns have become blended. This persevered improvement of IoT advocated the expansion of sophisticated and complicated systems which appreciably adjust the community. However, these technologies have guided to a brand new threat to the security of grids. Many present-day malware assaults, targeted at classic computer systems linked to the Internet, will also be required for IoT gadgets. With those enhancements, malicious actors have found new methods to control their weaknesses. One of the biggest cyber-attacks in instances of terabits in step with 2d operated, infected IoT gadgets harmonized within a botnet provides a massive DDoS assault which disrupts the Internet range for large geographic regions. This attack underlines the increasing hazard posed via uncertain IoT devices. Moreover, attacks that include those are evolving as greater threats as a larger quantity of exposed gadgets is introduced to networks throughout the globe. Their actions are anomalous and higher are the numbers of hazards and assaults toward IoT devices. Cyber-attacks arent new to the IoT, however as the IoT may be deeply interwoven in our lives and societies, traditional protection resolutions are inadequate when managing these dangers. Oftentimes, safety answers are created to run locally on host appliances, i.e., antivirus software, or as standalone machines (i.e. community firewalls and intrusion detection structures (IDSs). However, the IoT has obtained a clean set of community protocols, together with Zigbee, Ant+, and 6LoWPAN, that traditional safety solutions, such as rule-primarily based firewalls and host-based total antivirus software programs, had been not equipped with or have no longer been revised to account for. Moreover, many IoT gadgets suffer from computational, storehouse, or network situations. Due to those constraints, IoT safety answers, especially an IoT IDS, must be lightweight enough, in phrases of the computational, garage, and networking resources, to be living on the devices but sturdy enough to accurately hit upon potential intrusions. Therefore, a holistic method needs to be regular while coming to IoT intrusion detection. IoT devices cant be considered in a vacuum as self-contained machines due to the fact a totally fledged, modern protection answer is just too aid-annoying for constructing on those gadgets. The normal safety of the network necessitates IoT gadgets to be included as associates within a security answer rather than as man or woman nodes. Therefore, green protection of IoT devices could keep millions of net customers away from malicious moves. However, present malware detection techniques are afflicted by excessive computational complexity. Hence, theres a real necessity to protect the IoT, which has therefore resulted in a requirement to completely recognize the threats and assaults in an IoT infrastructure. 2024 selection and editorial matter, Mayank Swarnkar and Shyam Singh Rajput; individual chapters, the contributors. -
Idiosyncratic Deals: Understanding Effect of Intrinsic and Extrinsic Motivation I-Deals on Innovative Work Behaviour
I-deals or Idiosyncratic deals are specialised, adaptable work patterns by mutual agreement between employees and their managers to meet demands of a dynamic work place. Innovative work behaviour also known as IWB is referred to as the employee behaviour that intends to create and introduce novel and valuable products, processes, innovations and ways of working within a job-role or work-group of an organization. This research discovers the connection between various types of intrinsic and extrinsic motivational deals such as the work responsibility idiosyncratic deals, flexibility deals and financial ones and innovative behaviour, specially within the purview of the working women. It also provides an overview on the outcome of these deals on innovation at a workplace. Our study adopted descriptive research to assess the association of Idiosyncratic deals with IWB using a quantitative study across 352 female employees of Indian Corporate sector. It was found that there exists a direct and positive association amid intrinsically and extrinsically motivated Idiosyncratic deals and an innovative mind-set, in the context of Indian IT sector. This study establishes the influence of idiosyncratic deals and the motivational factors within them in driving an innovative mind set. Thus, the study helps to recognize the value that I-deals brings in establishing an effective innovative environment for employees playing a vital role in the growth of the organization. 2024, Iquz Galaxy Publisher. All rights reserved. -
Ideological preferences versus national integration of India
[No abstract available] -
Identity-based message authentication scheme using proxy vehicles for vehicular ad hoc networks
Message authentication verifies the identity of the sender vehicle, ensuring it in between vehicles and Road Side Units (RSU) is an essential part of Vehicular Adhoc Networks. Signature verification in RSUs will be troublesome if a large number of vehicles enters in its region at the same time. In such cases the efficiency of the RSUs will be affected due to high computational overhead. To address this issue, proxy vehicle based message authentication scheme (ID-MAP) is proposed by Asaar et al. (ITVT 67: 5409, 2018). It uses proxy vehicles to reduce the overheads of the RSU by verifying multiple messages at the same time. Even though it deals with the efficiency issues of RSU, the computational cost of signature generation is high. Since the ability of a vehicle to act as a proxy vehicle is based on the number of signed messages, it has a major impact. It also cannot guarantee privacy preservation and hence it is insecure against attacks based on privacy preservation. It also has other drawbacks like storage issues and high overheads. Hence, a new identity based message authentication using proxy vehicles is proposed in this paper. Elliptic Curve Cryptography based scheme is used without pairings for message authentication. Proxy vehicles will verify multiple messages from vehicles through batch verification and send the result to the RSU. The identity of multiple proxy vehicles will be verified by RSU, it can also cross check the correctness of the received result. Thereby RSUs can verify a large number of messages at the same time with the help of proxy vehicles. Security analysis shows that if each proxy vehicle verifies 300 messages of its neighbor vehicles, then with the help of proxy vehicles an RSU can verify 226,244 messages per second which is 40% less than that of ID-MAP scheme. It also shows that the computational cost to generate a signature in the proposed scheme is 50% less than that of ID-MAP scheme. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Identity verification in heterogeneous alliance network using blockchain and cryptography techniques /
Patent Number: 202141035794, Applicant: Abolfazl Mehbodniya.
There is a serious issue for the wireless transmission research community when it comes to data transfer under a scalable networking architecture. Data integrity, data quality, and originality must be maintained along the transmission chain. As a result, the relationships between data inside interference are a significant obstacle. Due to insufficient infrastructure for resource allocation and mapping the target address efficiently, in P2P transmission lines, the efficiency of the system is hampered. -
Identity in Consumption: Reading Food and Intersectionality in Anita Desai's Fasting, Feasting
With the resurging interest in Food Studies, this rapidly emerging field of study has seen multiple disciplines adding in their distinct flavours that truly make this an area to savour. Literary food studies, in particular, has become a relevant field of study with the understanding that food in literature always plays a symbolic role, as food in literature is never depicted for the sustenance of the literary characters. This paper seeks to explore the novel Fasting, Feasting (1999) by Anita Desai through the lens of food and foodways to explicate how the characters interact with the culinary arena, and ultimately, interact with each other and themselves. These interactions will serve as crucial insights into their identities, particularly their intersectional gender identities considering the facets of nationality, class, and the like. A special focus will also be rendered on the notion of marginalisation seen in the text, of which gender is a crucial deciding factor. The title of the novel hints at consumption-at both its presence and absence-which will prove as the gateway to the interactions of the characters with food in the novel to examine who it is that gets to feast while who are forced to starve. 2022 Aesthetics Media Services. All rights reserved. -
Identity formation and construction of communities among the users of social networking sites
Study of social networking sites and formation of community within the social networking sites is a new topic. Emergence of social networking sites and its impact on the social life is therefore a recent phenomenon. The social networking sites are a common platform for users to come together on the basis of common interest, ideas and opinions. Its existence and relevance is justified by number of factors operating together, such as large user base, radical changes in the process of socialization and impact of social media on our everyday life etc. What makes social networking sites so interesting is the fact that it is user centric. The very foundation of social networking sites was laid to facilitate socialization among the users. India has one of the largest social network user bases especially for social networking sites like Facebook and Orkut. This is even truer for urban centers such as Bangalore, Delhi, Mumbai and Chennai. The use of social networking sites is so common among the youth that it almost seems as though if one is not part of social networking site one does not have any social life. Everything we have in real life gets replicated in the online communities, the good and the bad. Therefore, this study is an attempt to understand how the users are able to come together and form community in the cyberspace. The researcher also attempts to study the impact of the same in the real life and vice versa. Since the advent of social networking sites it has radically changed the way we socialize. This study also looks at how social networking sites and social network analysis emerged. Identity formation is yet another aspect of the study; online identities are very fluid as one has to type themselves into existence. Therefore, the identities people take online are varied and often may be completely different from the reality. This aspect of fluid identity has both positive and negative aspects as we will see later in the thesis. Social media technologies are woven into the very fabric of our social life. As mentioned above are the various aspects of the social networking sites that we are looking into. The dissertation is divided into five chapters, the first chapter introduces one to the topic, along with aims, objectives, need and background of the study, the second chapter consists of the reviewed literature, the third chapter deals with the methodological part of the dissertation as various tools and techniques used in the study are explained, while the fourth chapter is the analysis and interpretation of the primary data collected, it is presented using various bar diagrams and tables, and the fifth chapter brings out the important findings in the study and also in the conclusion chapter. The fifth chapter summarizes all the findings of the earlier chapters. Finally, the dissertation consists of the bibliography list and the questionnaire which was distributed to collect the data. -
IDENTITIES AT THE DINNER TABLE: COMMENSALITY, SELF-PERCEPTION, AND RELATIONSHIPS IN ANNE CHERIANS A GOOD INDIAN WIFE
Food studies is rapidly gaining ground as a multidisciplinary area of research. Within it, literary food studies brings an interdisciplinary perspective as works of literature are viewed through the lens of food that is informed by frameworks and concepts that are rooted in a variety of fields including cultural anthropology, sociology, and more. one such concept that is in focus here is that of commensality that is associated with food and food practices. Commensality, drawing from notions of conviviality, refers to the practice of sharing a table and consuming food together. Deeper meanings of communal identities come to the fore in this social practice, leading it to shape how identities are understood and projected. Commensality can be a complex site of belonging and alienation depending on the context, and this paper seeks to explore the representation of the same in Anne Cherians A Good Indian Wife (2008). Leila, the titular Indian wife in the novel, moves to the US from India after her marriage to Neel and grapples with finding her place in the foreign land. With this displacement comes the endeavor to reaffirm her new identity, which now includes the role of being a wife and the aspect of being an immigrant. Neel also deals with complicated feelings towards the projection of his identity. With food playing a crucial role in the everyday experiences of their lives, commensality becomes a point of enquiry into how they see themselves and how their relationships with each other and themselves evolve through the course of the narrative. 2024 Nayana George. -
Identifying Wage Inequality in Indian Urban Informal Labour Market: A Gender Perspective
This chapter elucidates the wage differential between male and female informal workers in urban labour market by using employment and unemployment survey 61st (2004-2005) round, 68th (2011-2012), and Periodic Labour Force Survey 2019-2020 data of National Sample Survey Office (NSSO) unit level data. This study found that gender inequality not only increased during getting job but also persists after getting job during wage distribution. Based on the Oaxaca-Blinder (OB) decomposition, it is revealed that gender wage inequality is more in the labour market due to the labour market discrimination, that is, unexplained components. Hence, this study helps researcher, policy makers and government to fix the gender wage discrimination issues exist in the Indian labour market. This will enhance economic growth through the rise of the women labour force participation. 2024 A. Vinodan, S. Mahalakshmi, and S. Rameshkumar. -
Identifying the population of T-Tauri stars in Taurus: UVoptical synergy
With the third data release of the Gaia mission, Gaia DR3 with its precise photometry and astrometry, it is now possible to study the behavior of stars at a scale never seen before. In this paper, we developed new criteria to identify T-Tauri stars (TTS) candidates using UV and optical color-magnitude diagrams (CMDs) by combining the GALEX and Gaia surveys. We found 19 TTS candidates and five of them are newly identified TTS in the Taurus molecular cloud (TMC), not cataloged before as TMC members. For some of the TTS candidates, we also obtained optical spectra from several Indian telescopes. We also present the analysis of distance and proper motion of young stars in the Taurus using data from Gaia DR3. We found that the stars in Taurus show a bimodal distribution with distance, having peaks at 130.17-1.241.31 pc and 156.25-5.001.86 pc. The reason for this bimodality, we think, is due to the fact that different clouds in the TMC region are at different distances. We further showed that the two populations have similar ages and proper motion distribution. Using the Gaia DR3 CMD, we showed that the age of Taurus is consistent with 1Myr. 2023, Indian Academy of Sciences. -
Identifying the Existing Oral Proficiency Testing Patterns
The research aims to identify the different activities or patterns used for the teaching and testing of oral proficiency. Furthermore, the issues in the assessment of oral proficiency are also analyzed. The data was collected from the English teachers teaching in the selected Aided Kerala State Syllabus Schools in Trivandrum, Kottayam and Pathanamthitta districts from the grades 7th, 8th, 9th and 10th. The present study incorporated an exploratory research design based on a qualitative approach. The sample size consists of eleven teacher participants that were selected based on purposive sampling. The research study was divided into three phases. The phase 1, consists of open-ended questionnaire which were distributed to eleven teachers and the data obtained was categorized into different themes based on the responses from the teacher participants. Phase 2 consists of classroom observations of eleven teachers in which three teaching sessions per teacher and a total number of one thousand two hundred eighty-seven students were observed based on the classroom observation checklist. Moreover, phase 3 consists of interviews among the eleven teacher participants to gain further insights. The findings of the present research based on the analysis of the phase1, phase 2 and phase 3, indicates that the Communicative Language Teaching (CLT) approach is an effective approach to enhance the oral proficiency of the students. Moreover, the teaching and the testing patterns implemented by the school teachers are considered effective as it enables them to teach and to assess the oral proficiency of the students in a systematic manner. The research findings based on the triangulation prove that the use of reading, role play and storytelling are found to be consistent across the three phases and are commonly used by the teachers to enhance the oral proficiency of the students in the English language viii classrooms. Moreover, in the triangulation of assessment of oral proficiency, it has been observed that the activities such as reading and role play are found to be consistent across the three phases and are commonly used by the teachers. Furthermore, regarding the issues in the assessment of oral proficiency, lack of time is considered as one of the issues that is consistent across the three phases. The overall analysis of this research indicates that there is a positive or a parallel impact between the CLT approach and Theory of Knowledge (TOK) on the development of the oral proficiency of the students. The researcher suggests that there should be a standardized assessment tool to test the oral proficiency of the students in order to ensure grading consistency among the test assessors in the Kerala State Syllabus Schools. -
Identifying Social-Cognitive Factors Influencing Aggression in Adolescents: A Cross-Sectional Indian Study
Adolescence is a critical period during which the likelihood of experiencing self-regulation failures like aggressive outbursts is increased. Recent Indian studies on adolescents have reported an increasing incidence of aggressive acts during this time of transition, which is a threat to the adolescent, the victim and society in general. This study focuses on the social-cognitive perspective, implying that aggression is a social behaviour that is largely affected by ones beliefs about the acceptability of aggression and the degree of cognitive and effortful control they have over their emotions. Such beliefs are likely to be influenced by emotion socialisation, wherein parents and peers act as key agents. With this perspective, the current study, through a mediational model, explains the social-cognitive factors predicting aggressive behaviour in adolescents. This is a cross-sectional, descriptive study carried out on a sample of 475 adolescent students from the Delhi-NCR region recruited through purposive sampling. The data were collected through self-report questionnaires from schools and colleges. The model was tested using SPSS AMOS and was found to be a good fit for the data. The findings of this study are crucial from a risk and intervention perspective. It emphasises the need to build socially and emotionally competent students who not only have the skills needed to succeed but also nurture healthy social relationships and maintain positive mental health through adaptive emotion regulation skills. 2024 Department of Psychology, University of Allahabad. -
